{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " you are good!!\n"
     ]
    },
    {
     "data": {
      "image/png": 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Dzm3eAE61fTVwk6St4wofERHFjMXc9kdtf7N5+k3g4bbvbJ6vlbSRMpnzpC3A6cBE8/xm\npop+RESMyZzazCU9BrgKWDOyeB+wATgwsmwNpUlmf/N8P7B+4TEjImImM7aZA0haB/yA7bdLetLI\nS6uAncDKkWV7gV1MXa2vAm470ra3bdt29+PBYMBgMJhr7oiIZWE4HDIcDmddT7aP/KJ0NHCO7bc2\nz88DLrY9Iel82xdIeoPt10kS8DrgTcBrbF8o6dHAibY/OM22Pcu+gSO/Pjdipn3MaQsLzlFDhlpy\n1JChlhw1ZFh4jhoy1JKjrQySsK3Dls9SUC8EjgP2UJpL3gk8ALgV2GP7BkmbKFfiK4DrmkJ/BnAQ\nONb2FUfYdop5axlqyVFDhlpy1JBh4TlqyFBLjqqL+TilmLeZoZYcNWSoJUcNGRaeo4YMteToupjn\npqGIiB5IMY+I6IEU84iIHkgxj4jogRTziIgeSDGPiOiBFPOIiB5IMY+I6IEU84iIHkgxj4jogRTz\niIgeSDGPiOiBFPOIiB5IMY+I6IEU84iIHkgxj4jogRTziIgemHVCZwBJDwV+3/YzJa0GzgJuB3bb\nvl7SZmATsBrYbnu3pAHlzWK97UvHEz8iImAOV+aS7g2cMLLoZcDltq+iFHWAs21fafsy4FxJxwCn\n2r4auEnS1sUOHhERU2Yt5rb32/7YyKLTbN/ZPF4raSNlQudJW4DTgYnm+c1MFf2IiBiD+bSZrxl5\nvA/YABw45PXjgf3N8/3A+nmli4iIOZlTm/kh7hh5vArYCawcWbYX2MXU1foq4LbpNrRt27a7Hw8G\nAwaDwTziRET013A4ZDgczrrefIr5P0haZ3sC2Gt7h6QdAJIE3AhcS2lqATgFuGK6DY0W84iIONyh\nF7oXXHDBtOvJ9qwbk/QY4FJgK7ADOBO4Fdhj+wZJmyhX4iuA62xPSDoDOAgca/uwYi7JM+27vC/M\nnm2W5Mzl/zfjFhaco4YMteSoIUMtOWrIsPAcNWSoJUdbGSRhW4ctX+hBnK8U8zYz1JKjhgy15Kgh\nw8Jz1JChlhxdF/PcNBQR0QMp5hERPZBiHhHRAynmERE9kGIeEdEDKeYRET2QYh4R0QMp5hERPZBi\nHhHRAynmERE9kGIeEdEDKeYRET2QYh4R0QMp5hERPZBiHhHRAynmERE9MJ9p4+ZM0rOBPcBRtv96\nnPuKiFjOxnZlLun7gW/Y/ihwiqTjFncPw8Xd3LwNuw5AHRmgjhzDrgM0hl0HoI4MUEeOYdcBGsOx\nbXmczSxnAp9rHu8Anra4mx8u7ubmbdh1AOrIAHXkGHYdoDHsOgB1ZIA6cgy7DtAYjm3L4yzmxwN3\nNo/3AevHuK+IiGVtnMV8F7C6ebwKuG2M+4qIWNa00Fmxj7hh6XHABtt/Kelc4D22vzby+nh2HBHR\nc7Z16LKxFXMASVspV+T3tj0c244iIpa5sRbziIhoR24aiojogRTziIgeWLLFXNKJkjYsxxySTmhz\nf/dE1z8XSc+QNOhq/zXlqCFDLbo6Fm2eq0uimEv6VUn3GXl+PPAc4H3LLYekY4CPS7rvIctPaSvD\nyD47Ox6SPtR8VfP1BElPB55N6Qrbihpy1JBhhmwPlHS/FvdXzbFo+1xdEsUc2ACcLOlkSU+2vcv2\n7wHfXE45JD0KOAi8mcN/MS9qI8Mhujwex0k6C3ifpGcBbwM+A3yeqZvV2lBDjhoyACBphaSjJG2S\ntBL4dZoxoJqM41bFsejiXB3rQFuLoemjfjXlgBwNvEDSI4C7gJuWWY6XAx8EbgHOl/RWwMBu4F9b\nygBUcTw+DPwt8FfAe4DrbX9J0udo9wqshhw1ZJj0iObfM4H3U35HniTpI8APAleMef+1HIvWz9Xq\niznlTtKvA58CngTcDHwR+IDb7VdZQ47/ARwH3A/4J2BAKZ6rgC+3lGFS18djCDwQeCRwDnCipGdQ\nTp6HtbD/mnLUkGHSMyhXpEcB3w9cCZwM/BnlKn3chtRxLFo/V5dCM8sHKe9o5wMfoRSPr9LOL0Zt\nOV4AfB/wIErx3AM8AHhp87VNXR+Pf6UUiY8Ae2xfD9xAeUP5npYy1JKjhgyTPgD8P+BdwF5KAXsE\n8F4WfbC9adVyLFo/V6u/aUjSq4E1wMeAZwEX2d4l6QHAE22/d7nkaD5Q+R3KB4wbgXsDfwS8Alhv\n+zfGnWEkS6fHQ9JG4FXAV4AVwMrm6/2BU20/fpz7rylHDRkOybMZOED5y+0xwNm2Xy7pR21fOeZ9\nV3EsujhXl0IxfxDwROBWygduf095t7+LMl76vuWSQ9JRlPbpHwWutn37yGvvtv0T484wsr/Oj0fU\nR9KPAPspV6V7gHWUAfcuBu60/Y0O47Wmi3O1+mIOIOlsShutKO9w9wMeDnzR9juWYY7NwM8Dr7f9\n1WbZ/UZ/YVrKUcXxiHpIOgf4NPAt4LcpbdXvowyJvcb2m7tL1742z9UlUczjcJLuZfvbXeeIw0la\nAZxhe3sH+94I7LTddrfd6bI8D7gG+CngzbYPdpRjE7Cxq8H+2jpXl8IHoNNq7uhqrTeOpHs37WCd\nk7QFeFzXOabT5s9F0pMlfV7SGyU9t2mvr8Ezged1tO/XU3pR1OAy2zuB3wUe3GGOl9P+B8FAu+fq\nki3mwKuBNq9MXwZ8b4v7m8kLKc0aNWrz5/JoylXfXwCnA78l6a8ktXZsJN23OWEZ2e83KR/AdeHb\nlM8tOndIF9UHtnWXsqQHNzcsTdpLdz+P1s7VJVPMJb1Q0mgx/VLLzQz3onxCj6QfkvSQFvd9N5Wx\nHh5P+cARSadJWiXpAx3l6fLn8nng07Y/Tuk18dfAq23vb2n/ACdQuqEBTH5O8BW6K6ifocNb+NWM\nyyNpnaSjJT2e8uZ2AlPHZ9yey3deDd9CBz+Pts/VpXDT0KQvUG4E+Ezz/Ist7/9fmTpePwf8l5b3\nP+mXgdcCb5N0CbCZckPC73SUp8ufyy7gjZJ2Ufq938f2jS3uH+D/M9WEcJekdZQePquP/C1jz3M8\n7d9ENul5TRH7NPDdlAugh9r+35La6jr7Wcp5cU3z/MuULopta/Vcrb6YN7eN3xe4A3hU0259gDIm\nyArb32opyr8B50j6FOVkfb6kyambdtv+4Dh3Lulk4KeB36P06/6flJNlN+Wq55/Guf9p8tTwc9lF\nc/u27Ymmd02rbH9b0p7m6Scohf0zlH7NXbiF8ntxfRc7t/2WponjhcCfUGrMepURC9uaB/h64IdG\nnu+kNMm1oqtztfpiTunw/zHKIDnXUTKvoLz7bqQU2TZ8oclwJaWNdiXlppmNtPMn3J2UfruvpHT5\n+jGmBg76GOVDtzZHkazh57IL+AVgs6S9wA2SHjDZBaxFf998/QfgtqbAd3ElCPAlyu9CJyT9EqX5\n6xuUz5h2NJlWUYrZ2DU3r42+cdxGKaJt6eRcrb6Y237rdMslHaD82dJKMbe9T9Jdzafzo1r5s972\nrcDvNu/6F1GuPj5Lacs/EThN0kdtT7SUp/Ofi+07JF1DuSL+bsrV2D7KsAKtsf2u5usnRxZ3dWV+\nO932dHox8AeUn8lGSvv1/SmDr72yxRxvG3l8O+X+h1Z0da4umQ9Ap/El4Ada3mfnvVls3wKcR+l+\ndo3toe2/sP3atgr5LNr+uTwbOJNyYXI58MmZV29Nmx/CHqqTJpbG2yjNGk8FTqUU9oOU8UjuaCvE\naJ/2ps/9oRdhbWS4hRbP1SV701DTl/kdtl/S4j5fYvudbe1vJioD3n+/7b/pOsuoLn4uNZJ0n+Vy\n6/p0JP0BZWyWO4AJytC3D7L9iU6DdaCtc3XJFnMod9q1+AFodSQd3dVddTPp8uci6UTgW9M0hy27\nHDVkaHKspoxR8hXb18y2/pgydHos2jhXl0Qzi6TDckp6LNDq1d+Rckh6WZs5Jtk+qDKjy6CL/cPd\nd8aePLqsrUKuCqbxqyVHDRlm8L3Aj9NSj5Iaj0Vzrq6Q9KRx7WNJFHPKiGsASHpR0yXwIuCjyzTH\nqE5uVZY0OdD/RuAJbe+/kekE68pwt9GhL5qmlVcAP9vS7qs6FiPGOsxD9b1ZGqM3YGylDHT//A4+\n8Os8h6QHU/q1T3Z16upW5d9WGSHvs8DbJZ1K+aDrAKWN9F22x3bjirqftq6aHDVkGMmyATgNuI+k\nD0wOhdzcB7C3hf1XcSyadvINtm+UdO/mruSxDvNQdTFvbgL5MvB5SS8CtgDrgV8C1kr6gu0/XC45\nGs+lzOQy2fZ4C93cOv48yrRcdwB/R5lv8TOHjMcxTl1PW1dTjhoyjGY5mXLH9P0oXUUnr9Tb6M1S\ny7GYHObhNyjDGPwUYx7mofZmlrWULk6PpNykcxHwbttvsP0rlIlbl1MOmLpVedKXgdZHc7R9gHKl\n8y+UuzAfCZwn6SdbitD1tHU15aghw6RfbrI8Bvivkt4g6bVNlte0sP9ajkXrwzxUfWVu+2KAZiCn\nbZR39ns37bV7bH9qOeVodHqr8iRJj6OMkPiXwOcofb3fBeyRtKGFXgOvoNyB+1fAm5iatu4mSWe7\npekEK8lRQ4ZJ11AuMFZTxjD6GvD2Fgc/q+JYdDHMQ+1X5pNuBu6wfUnz/BGUd/3/ttxy2N7Fd45x\n0fatypNWUG7Z/hTlT8g1wEMoXdAe2cL+30P5eYhysqxpup+JMuRCW2rIUUMGAJquh6dRastu4G+A\nC5vPVNpQzbFgmmEeGOOAX0umn7mmma1D0nrbbQ3eU02O0T6rzU06f2z7xW3tfyTHH1Imqf0BSrvk\nQeDfgevb6J6oSqatqyFHDRmmyXSx7Z9tHr8SuLy5K3Lc+63uWIxke7/t54xl20ulmMeRSbrQdhft\no5P7/1VKt837UiZ5vriDD96iMpI0+nsg6Ym22/x8qTqS/o/tF45l2znnYqEkPdj2l7rOEVG7cQ7z\nsFTazIOpWVxGnv+wpB/uKs+k0UIuqbXRAiU9R2Umm07VkKOGDLWo4Vgc6Vwd53g9KeZLy1Mk3X/k\n7stnAE+QdG3bQSSdJOn7Dll2FPBbLcb4GeC1ki6ebcVlkKOGDLX4Gbo/Fq2fqynmS8teygc5r5f0\nK8A/UrpftdF/91DHAT84zfLWhjkF3mP7WcAnJK1pcb815qghQy1qOBatn6tV9zOPw3yZMmPJ3wHH\nAicBjwIONl2//s3211vK8i/A00YX2P6mpH1t7FzSjwMPawYuWg08XdKXKW8mXwd2tvEhbA05ashQ\ni4qORevnaq7Ml5Y3U35Bf5zSDfDrwG8CDwQeCzy0rSBN18h7SdqsMnLj8ZK+i/Z+px5OGXtjNaWv\n/UmUiYwfRrmp6iHLKEcNGWpRy7Fo/VxNb5YlRNJ2yh2oWymz6uyiTJf2eNsXdJDn1yl3oB6kDGz0\nUMov78Ob2/3Hvf8nUf5C+HfgybavGvc+a81RQ4Za1HAsujhX08yytDwV+Enbr1EZQ/wsyl2Y75b0\nFNutDcUr6RXA/7L9RUknAfe1/UeUsTnacjulf/snKXeidqWGHDVkqEUNx6L1czVX5kuMygQZKw6d\ntUTSw9scI0bSi23/qaStwBcof9q+jDJ2zCW22xjudDVwl8scj52pIUcNGWpRy7Fo+1xNMY8FaW6d\nfn8zsNB9KBMQ/NHIeOsR0YJ8ABoLdTllcC1sf8P277dVyFXJNH415KghQy2W67FIMY+FehawQZIA\nJLXWo4Z6pvGrIUcNGWqxLI9FinnMW9M2+TzKmOaXqExp19Y8j3D4NH4rKdP4fa7FDLXkqCFDLZbl\nsUibecxLc5vyU4BLgJdQptL7M0rf3lvG2TVRU9P4PYvSW2ELcDplZpm1QNvTCXaWo4YMtVjuxyJd\nE2O+fprS1epoyo0ZX6KMa34vShv6k8a477WUE/WRlIkILgJeZPttUHoLjHHfteWoIUMtlvWxyJV5\nzJukoymTOn+ccofbj1AmmN7exjRhmprG7y8osy19iDKN39hmQK81Rw0ZarFcj0XazGNemgkpBNwA\nrKP0Nf9zwC3O99j5NH4V5aghQy2W5bHIlXnMi6THAj8GfJrSvPJvwAHK2BPftv2GlnJ0Po1fLTlq\nyFCL5XgsUsxj3iStBDYDnwV+BXiL7YnpTqSIGK8U81gUzY0aW2x/uussEctRinlERA/kA9CIiB5I\nMY+I6IG13mwEAAABg0lEQVQU84iIHkgxj4jogRTzWDYkPUrS++fxfQ+Q9PfTLH+VpPsvTrqIhcnY\nLLFs2P5nSf8+j+/7qqQbp1n+lsVJFrFwuTKPXmuuqlfPvuZh37dpDuscK2nV/JJFLK5cmUffnQYc\nI+k44PHAGkk/ATwd+BPKmDK/B7wA+EXKOfFe4KmSvgD8WrMuzXynj6HM+v5Wylg0P9dsI6JTuTKP\nvvsw8DfA04BfAL5p+93AhcBTbO8EvtFMuvuPALY/Z/sdlIkNzrV9V7Otq2z/JvBo298CDmtHj+hK\ninn0msstzn8AnE8Ze31yRMdvAysmV2u+avL7JL0c+Afg5mYMGkaKekR1Usyj1ySdB9wFPAh4C3Cy\npJOA7wFOkvRdwE5Jvww8ljKf6RnA84EdlAkO1jbLT5P0IGCjpI3AQykDjUV0LmOzxLIhSbY9+XUh\n3zc5MqSkFU2TS0SnUswjInogzSwRET2QYh4R0QMp5hERPZBiHhHRAynmERE9kGIeEdEDKeYRET3w\nH/D5A1jDalFeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xeb37ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import re\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "aticle = open(r\"E:\\EMC\\WifiNet\\three.txt\",'r')\n",
    "file = aticle.read()\n",
    "pattern = r'(.*?),(.*?),(.*?),(.*?),(.*?),(.*?),(.*?),(.*?),.*?'\n",
    "data = re.findall(pattern, file)\n",
    "df = pd.DataFrame(data=data, columns = ['bianhao','zhuzhi','xuehao','shuzi','wangzhi',\n",
    "                                        'leixing','fuwuqi','qita'])\n",
    "zhuzhi = df.groupby('zhuzhi')\n",
    "dfa = zhuzhi.count()\n",
    "Sorted = dfa.sort(columns = 'bianhao',ascending = False)\n",
    "last = Sorted[:10]\n",
    "last['bianhao'].plot(kind = 'bar')\n",
    "print(' you are good!!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "Required argument 'path' (pos 1) not found",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-60c3ba30e1c3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchdir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: Required argument 'path' (pos 1) not found"
     ]
    }
   ],
   "source": [
    "os.chdir()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "os.chdir(r'E:\\EMC')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'E:\\\\EMC'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.getcwdb()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
